added .readthedocs.yaml + minor edits

parent bae61f93
# .readthedocs.yaml
# Read the Docs configuration file
# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
# Required
version: 2
# Set the OS, Python version and other tools you might need
build:
os: ubuntu-22.04
tools:
python: "3.9"
# You can also specify other tool versions:
# nodejs: "19"
# rust: "1.64"
# golang: "1.19"
# Build documentation in the "docs/" directory with Sphinx
sphinx:
configuration: docs/conf.py
# Optionally build your docs in additional formats such as PDF and ePub
# formats:
# - pdf
# - epub
# Optional but recommended, declare the Python requirements required
# to build your documentation
# See https://docs.readthedocs.io/en/stable/guides/reproducible-builds.html
# python:
# install:
# - requirements: docs/requirements.txt
\ No newline at end of file
......@@ -35,7 +35,7 @@ Predictions are compared with the STRING database. Optionally, the graphs can be
The original SENSE-PPI repository contains two models (checkpoints with weights) pretrained on human PPIs: `senseppi.ckpt` and `dscript.ckpt` pretrained on SENSE-PPI and DSCRIPT human datasets respectively.
- `senseppi.ckpt` (preferred) : Download from [here](http://gitlab.lcqb.upmc.fr/Konstvv/SENSE-PPI/raw/master/pretrained_models/senseppi.ckpt)
- `senseppi.ckpt`: Download from [here](http://gitlab.lcqb.upmc.fr/Konstvv/SENSE-PPI/raw/master/pretrained_models/senseppi.ckpt)
- `dscript.ckpt` : Download from [here](http://gitlab.lcqb.upmc.fr/Konstvv/SENSE-PPI/raw/master/pretrained_models/dscript.ckpt)
The package already comes with preinstalled model `senseppi.ckpt` that is used by default if model path is not specified.
......
import numpy as np
from torchmetrics import AUROC, Accuracy, Precision, Recall, F1Score, MatthewsCorrCoef
import networkx as nx
import seaborn as sns
import matplotlib
......
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